Update app.py

app.py

@@ -6,41 +6,48 @@ import faiss
 import numpy as np
 from sentence_transformers import SentenceTransformer
 
-# ✅ Load vector store and data
+# Load files
 index = faiss.read_index("faiss_index.bin")
 with open("texts.json", "r") as f:
     texts = json.load(f)
 
-# ✅ Load embedding model
+# Embedding model
 model = SentenceTransformer("all-MiniLM-L6-v2")
 
-# ✅ OpenRouter setup
+# API key
 API_KEY = os.environ.get("OPENROUTER_API_KEY")
 MODEL = "deepseek/deepseek-chat-v3-0324:free"
 
-# ✅ Helper: Find top-k relevant context
+# Function: Get relevant chunks
 def get_relevant_context(query, k=5):
     query_vector = model.encode([query])
     scores, indices = index.search(np.array(query_vector), k)
     return [texts[i] for i in indices[0] if i < len(texts)]
 
-# ✅ Chat logic
+# Chatbot logic
 def chat_with_data(message, history):
-    greetings = ["hi", "hello", "hey", "salam", "assalamualaikum", "good morning", "good evening"]
+    greetings = ["hi", "hello", "hey", "salam", "assalamualaikum"]
     message_lower = message.lower().strip()
 
     if any(greet in message_lower for greet in greetings):
         return "👋 Hello! How can I assist you regarding LogiqCurve today?"
 
     context = get_relevant_context(message)
-    if not context:
-        return "❌ Sorry, I can only answer questions related to LogiqCurve and its services."
+    if not context or all(len(c.strip()) < 10 for c in context):
+        return "❌ Sorry, I can only answer questions based on content from LogiqCurve.com."
 
     context_text = "\n".join(context)
-    prompt = f"You are a helpful assistant for LogiqCurve. Use only the following context:\n\n{context_text}\n\nUser: {message}"
+
+    prompt = (
+        f"You are a helpful assistant for LogiqCurve.\n"
+        f"ONLY use the context below to answer the user. Do not use any outside knowledge.\n\n"
+        f"Context:\n{context_text}\n\n"
+        f"User question: {message}\n\n"
+        f"Answer strictly using the context above."
+    )
 
     messages = [
-        {"role": "system", "content": "You are a helpful assistant that answers only using provided context."},
+        {"role": "system", "content": "You are a strict assistant who only answers using provided context."},
         {"role": "user", "content": prompt}
     ]
 
@@ -57,14 +64,16 @@ def chat_with_data(message, history):
     try:
         res = requests.post("https://openrouter.ai/api/v1/chat/completions", headers=headers, json=payload)
         res.raise_for_status()
-        return res.json()["choices"][0]["message"]["content"]
+        reply = res.json()["choices"][0]["message"]["content"]
     except Exception as e:
-        return f"❌ Error: {e}"
+        reply = f"❌ Error: {e}"
+
+    return reply
 
-# ✅ Gradio UI
+# UI
 gr.ChatInterface(
     fn=chat_with_data,
-    title="MK Assistant",
-    description="Ask questions related to LogiqCurve. Chat is limited to website-related content only.",
+    title="MK Private Assistant",
+    description="Ask me about LogiqCurve services. I respond only using website data.",
     theme="soft"
 ).launch()